Papers
2
Total Citations
26
H-Index
2
About
Fuyang Chen is a pioneering researcher at the intersection of artificial intelligence, multimodal perception, and music technology. Their work centers on developing intelligent systems that can interpret and respond to human emotional expression through complex, multi-channel inputs—particularly in the context of musical performance and conducting. Chen’s most significant contribution is the Fuzzy Multimodal Fusion Network (FMFN), introduced in 2024, which integrates auditory, visual, and gestural cues to enable robots to discern human emotions during ensemble conducting. This breakthrough, already garnering 17 citations, addresses a critical gap in human-robot interaction by modeling the inherent uncertainty and fuzziness of emotional communication. Additionally, Chen has explored the application of multi-criteria decision-making frameworks like AHP and MOORA to evaluate AI-enhanced music pedagogy, though this work has since been retracted. Despite this, Chen’s core research remains highly influential, demonstrating how fuzzy logic and deep learning can bridge the gap between artistic expression and machine understanding. Their work holds transformative potential for affective computing, collaborative robotics, and interactive arts education.
Research Focus
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Top Papers
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